scholarly journals Traffic-aware adaptive server load balancing for software defined networks

2021 ◽  
Vol 11 (3) ◽  
pp. 2211
Author(s):  
C. Fancy ◽  
M. Pushpalatha
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Efficient Algorithm ◽  
Software Defined Networks ◽  
Network Bandwidth ◽  
Complete Knowledge ◽  
Additional Processing ◽  
Load Balancing Algorithm ◽  
Network Status ◽  
Two Parameters

Servers in data center networks handle heterogenous bulk loads. Load balancing, therefore, plays an important role in optimizing network bandwidth and minimizing response time. A complete knowledge of the current network status is needed to provide a stable load in the network. The process of network status catalog in a traditional network needs additional processing which increases complexity, whereas, in software defined networking, the control plane monitors the overall working of the network continuously. Hence it is decided to propose an efficient load balancing algorithm that adapts SDN. This paper proposes an efficient algorithm TA-ASLB-traffic-aware adaptive server load balancing to balance the flows to the servers in a data center network. It works based on two parameters, residual bandwidth, and server capacity. It detects the elephant flows and forwards them towards the optimal server where it can be processed quickly. It has been tested with the Mininet simulator and gave considerably better results compared to the existing server load balancing algorithms in the floodlight controller. After experimentation and analysis, it is understood that the method provides comparatively better results than the existing load balancing algorithms.

A Two-Phase Load Balancing Algorithm for Cloud Environment

2021 ◽  
Vol 13 (1) ◽  
pp. 38-55
Author(s):  
Archana Singh ◽  
Rakesh Kumar
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Virtual Machines ◽  
Second Phase ◽  
Cloud Environment ◽  
Cloud Platform ◽  
Efficient Utilization ◽  
Two Phase ◽  
Excessive Load ◽  
Load Balancing Algorithm

Load balancing is the phenomenon of distributing workload over various computing resources efficiently. It offers enterprises to efficiently manage different application or workload demands by allocating available resources among different servers, computers, and networks. These services can be accessed and utilized either for home use or for business purposes. Due to the excessive load on the cloud, sometimes it is not feasible to offer all these services to different users efficiently. To solve this excessive load issue, an efficient load balancing technique is used to offer satisfactory services to users as per their expectations also leading to efficient utilization of resources and applications on the cloud platform. This paper presents an enhanced load balancing algorithm named as a two-phase load balancing algorithm. It uses a two-phase checking load balancing approach where the first phase is to divide all virtual machines into two different tables based on their state, that is, available or busy while in the second phase, it equally distributes the loads. The various parameters used to measure the performance of the proposed algorithm are cost, data center processing time, and response time. Cloud analyst simulation tool is used to simulate the algorithm. Simulation results demonstrate superiority of the algorithm with existing ones.

scholarly journals Regional Load Balancing Circuitous Bandwidth Allocation Method Based on Dynamic Auction Mechanism

2018 ◽  
Vol 176 ◽  
pp. 01020
Author(s):  
Wang Chao ◽  
Zhang Dalong ◽  
Ran Xiaomin
Keyword(s):  
Load Balancing ◽  
Bandwidth Allocation ◽  
Link Quality ◽  
Communication Overhead ◽  
Response Delay ◽  
Allocation Model ◽  
Network Bandwidth ◽  
Delay Increase ◽  
Link Model ◽  
Network Status

Aiming at the problem of link congestion caused by the shortage of network bandwidth resources at the user end, this paper first proposes a regional load balancing idea. Then, for the problem of bandwidth resource allocation in regional load balancing, a bandwidth allocation model is established and a dynamic auction algorithm is proposed. The algorithm calculates the link quality and stability by constructing a link model, and introduces the auction bandwidth to the auctioneer's incentive degree to obtain the auction bidding function. The simulation results show that the algorithm can effectively improve the user's network status, reduce the service response delay, increase the throughput, and at the same time can effectively prevent the auction user's false bidding behavior, so that the auction quote quickly converges to the maximum quote, reduces the number of auctions, and reduces Communication overhead.

OpenFlow-Based Global Load Balancing in Fat-Tree Networks

2014 ◽  
Vol 989-994 ◽  
pp. 4794-4798 ◽  
Author(s):  
Yu Wen Wu ◽  
Wei Zhang
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Essential Role ◽  
Data Centers ◽  
Cloud Services ◽  
Tree Topology ◽  
The Self ◽  
Internal Load ◽  
Tree Networks ◽  
Load Balancing Algorithm

Cloud services have been explosively popular over the last decade. And data centers play an essential role in providing cloud services. Inside a data center, any server instance has the chance to inject traffic of various applications into the network. Yet how to balance the enormous internal load to make the best of data center network is a highly prioritized problem to be solved. To provide balanced traffic in data centers, this paper proposes an OpenFlow-based GLB load balancing algorithm in data center fat-tree networks. GLB uses a path-related weight to select path. This weight indicates how balanced of a path. We implement GLB algorithm as a module in an openflow controller platform, POX. On the self-defined modified mininet emulation platform, we conduct experiments in a fat-tree topology environment running random traffic to generate performance data. Experiment results demonstrate that our proposed GLB algorithm outperforms DLB algorithm in terms of load balancing.

scholarly journals Path computation enhancement in SDN networks

2021 ◽  
Author(s):  
Tim Huang
Keyword(s):  
Load Balancing ◽  
Data Center ◽  
Management Approach ◽  
Distributed Network ◽  
Data Center Networks ◽  
Network Nodes ◽  
Path Computation ◽  
Shortest Path Algorithms ◽  
Load Balancing Algorithm ◽  
Hybrid Sdn

Path computation is always the core topic in networking. The target of the path computation is to choose an appropriate path for the traffic flow. With the emergence of Software-defined networking (SDN), path computation moves from the distributed network nodes to a centralized controller. In this thesis, we will present a load balancing algorithm in SDN framework for popular data center networks and a fault management approach for hybrid SDN networks. The proposed load balancing algorithm computes and selects appropriate paths based on characteristics of data center networks and congestion status. In addition, a solution that supports proper operations of a hybrid SDN network will also be proposed. The evaluation shows the proposed load balancing algorithm performs better than classic shortest path algorithms. We also demonstrated that the proposed solution for hybrid SDN networks can support proper operations in complicated hybrid SDN networks.

scholarly journals An Analysis on ECSE Load Balancing Algorithm with CDC as a Service Broker Policy in Cloud with Heterogeneous Communication and Device Characteristics

2019 ◽  
Vol 8 (9) ◽  
pp. 1631-1635
Keyword(s):  
Load Balancing ◽  
Response Time ◽  
Data Center ◽  
Data Centers ◽  
Cloud Data ◽  
Heterogeneous Device ◽  
Cloud Data Centers ◽  
Service Broker ◽  
Load Balancing Algorithm ◽  
Machine Allocation

Load balancing algorithms and service broker policies plays a crucial role in determining the performance of cloud systems. User response time and data center request servicing time are largely affected by the load balancing algorithms and service broker policies. Several load balancing algorithms and service broker polices exist in the literature to perform the data center allocation and virtual machine allocation for the given set of user requests. In this paper, we investigate the performance of equally spread current execution (ESCE) based load balancing algorithm with closest data center(CDC) service broker policy in a cloud environment that consists of homogeneous and heterogeneous device characteristics in data centers and heterogeneous communication bandwidth that exist between different regions where cloud data centers are deployed. We performed a simulation using CloudAnalyst an open source software with different settings of device characteristics and bandwidth. The user response time and data center request servicing time are found considerably less in heterogeneous environment.

scholarly journals Proposing a load balancing algorithm with an integrative approach to reduce response time and service process time in data centers

2019 ◽  
Vol 16 (4) ◽  
pp. 627-637
Author(s):  
Sanaz Hosseinzadeh Sabeti ◽  
Maryam Mollabgher
Keyword(s):  
Load Balancing ◽  
Data Processing ◽  
Response Time ◽  
Virtual Machine ◽  
Data Center ◽  
Processing Time ◽  
Data Centers ◽  
Virtual Machines ◽  
Overall Response ◽  
Load Balancing Algorithm

Goal: Load balancing policies often map workloads on virtual machines, and are being sought to achieve their goals by creating an almost equal level of workload on any virtual machine. In this research, a hybrid load balancing algorithm is proposed with the aim of reducing response time and processing time. Design / Methodology / Approach: The proposed algorithm performs load balancing using a table including the status indicators of virtual machines and the task list allocated to each virtual machine. The evaluation results of response time and processing time in data centers from four algorithms, ESCE, Throttled, Round Robin and the proposed algorithm is done. Results: The overall response time and data processing time in the proposed algorithm data center are shorter than other algorithms and improve the response time and data processing time in the data center. The results of the overall response time for all algorithms show that the response time of the proposed algorithm is 12.28%, compared to the Round Robin algorithm, 9.1% compared to the Throttled algorithm, and 4.86% of the ESCE algorithm. Limitations of the investigation: Due to time and technical limitations, load balancing has not been achieved with more goals, such as lowering costs and increasing productivity. Practical implications: The implementation of a hybrid load factor policy can improve the response time and processing time. The use of load balancing will cause the traffic load between virtual machines to be properly distributed and prevent bottlenecks. This will be effective in increasing customer responsiveness. And finally, improving response time increases the satisfaction of cloud users and increases the productivity of computing resources. Originality/Value: This research can be effective in optimizing the existing algorithms and will take a step towards further research in this regard.

Towards An Implementation of A Modified Static Load Balancing Algorithm To Minimize Execution Time

2019 ◽  
Vol 12 (1) ◽  
pp. 69-74
Author(s):  
Hioual Ouided ◽  
Laskri Mhamed Tayeb ◽  
Hemam Sofiane Mounine ◽  
Hioual Ouassila ◽  
Maifi Lyes
Keyword(s):  
Load Balancing ◽  
Failure Probability ◽  
Execution Time ◽  
Static Load ◽  
Optimal Algorithm ◽  
Scheduling Algorithm ◽  
Static Load Balancing ◽  
Load Balancing Algorithm ◽  
Two Parameters ◽  
The Impact

Purpose: The aim of this article is to discuss the impact of static load balancing over a set of heterogeneous processors, where tasks are independent and unitary in static environments, by showing how to distribute task in order to optimize both the average response time and the degree of the resources used. Methods: Implementation of a modified scheduling algorithm, the latter is based on two parameters which are the execution time and the failure probability. The algorithm is based on the results of an optimal algorithm that already exists, with only one parameter that is execution time. Results: The obtained results show that the modified scheduling algorithm gives us the good results. Conclusion: The modified algorithm assumes that the processor has smallest execute time. So, the failure probability increases because of it’s frequently use. The results obtained by testing this proposed algorithm are better than the optimal algorithm.

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